Walking is the basic locomotion pattern for bipedal robots.The walking pattern is widely generated using the linear inverted pendulum model.The linear inverted pendulum motion of each support period can be designed as...Walking is the basic locomotion pattern for bipedal robots.The walking pattern is widely generated using the linear inverted pendulum model.The linear inverted pendulum motion of each support period can be designed as a walk primitive to be connected to form a walking trajectory.A novel method of integrating double support phase into the walk primitive was proposed in this article.The method describes the generation of walking patterns using walk primitives with double support,specifically for lateral plane including walking in place,walking for lateral,and walking initiation,and for sagittal plane including fixed step length walking,variable step length walking,and walking initiation.Compared to walk primitives without double support phase,those with double support phase reduce the maximum speed required by the robot and eliminate the need to adjust foothold for achieving continuous speed.The performance of the proposed method is validated by simulations and experiments on Neubot,a position-controlled biped robot.展开更多
This paper presents LQR sliding surface-based Sliding Mode Controller(LQR-SMC)for balancing control of a Rotary Double Inverted Pendulum(RDIP)system.It is a challenging research topic in control engineering due to its...This paper presents LQR sliding surface-based Sliding Mode Controller(LQR-SMC)for balancing control of a Rotary Double Inverted Pendulum(RDIP)system.It is a challenging research topic in control engineering due to its nonlinearity and instability.The RDIP system uses only a motor to control two serially connected pendulums to stand at the upright position.The sliding surface is designed based on the LQR optimal gain.Nonsingular gain matrix is obtained by using the left inverse of the input matrix in the state space form of the system dynamics.The Lyapunov stability theory is used to determine the stability of the controller.To evaluate the performance of LQR-SMC,some performance indices,including the Integral Absolute Error(IAE),Integral Time Absolute Error(ITAE),and the Integrated Square Error(ISE),are used.System stability can be maintained by LQR-SMC under external disturbances as well as model and parameter uncertainties.展开更多
基金supported in part by the National Key R&D Program under Grant 2018YFB1304504.
文摘Walking is the basic locomotion pattern for bipedal robots.The walking pattern is widely generated using the linear inverted pendulum model.The linear inverted pendulum motion of each support period can be designed as a walk primitive to be connected to form a walking trajectory.A novel method of integrating double support phase into the walk primitive was proposed in this article.The method describes the generation of walking patterns using walk primitives with double support,specifically for lateral plane including walking in place,walking for lateral,and walking initiation,and for sagittal plane including fixed step length walking,variable step length walking,and walking initiation.Compared to walk primitives without double support phase,those with double support phase reduce the maximum speed required by the robot and eliminate the need to adjust foothold for achieving continuous speed.The performance of the proposed method is validated by simulations and experiments on Neubot,a position-controlled biped robot.
文摘This paper presents LQR sliding surface-based Sliding Mode Controller(LQR-SMC)for balancing control of a Rotary Double Inverted Pendulum(RDIP)system.It is a challenging research topic in control engineering due to its nonlinearity and instability.The RDIP system uses only a motor to control two serially connected pendulums to stand at the upright position.The sliding surface is designed based on the LQR optimal gain.Nonsingular gain matrix is obtained by using the left inverse of the input matrix in the state space form of the system dynamics.The Lyapunov stability theory is used to determine the stability of the controller.To evaluate the performance of LQR-SMC,some performance indices,including the Integral Absolute Error(IAE),Integral Time Absolute Error(ITAE),and the Integrated Square Error(ISE),are used.System stability can be maintained by LQR-SMC under external disturbances as well as model and parameter uncertainties.
